ArticleJournal of machine learning research : JMLR2016
Fused Lasso Approach in Regression Coefficients Clustering - Learning Parameter Heterogeneity in Data Integration.
Article in Journal of machine learning research : JMLR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- Representation Retrieval Learning for Heterogeneous Data Integration.Journal of the American Statistical Association · 2026Article
- Sepsis in neonates with necrotizing enterocolitis: outcomes and predictive model.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments.Biometrics · 2026Article
- Distributed fusion R-learner of heterogeneous treatment effect using distributed medicaid data.Biometrics · 2026Article
- A partially heterogeneous weighted fusion learning method for potential heterogeneous treatment effect in multi-site survival study.BMC medical research methodology · 2025Article
- FEDERATED LEARNING OF ROBUST INDIVIDUALIZED DECISION RULES WITH APPLICATION TO HETEROGENEOUS MULTIHOSPITAL SEPSIS POPULATION.The annals of applied statistics · 2025Article
- Regarding: LASSO-derived model for the prediction of lean-non-alcoholic fatty liver disease in examinees attending a routine health check-up.Annals of medicine · 2024Article
- New clinical trial design borrowing information across patient subgroups based on fusion-penalized regression models.Statistical methods in medical research · 2024Article
- High-dimensional variable selection accounting for heterogeneity in regression coefficients across multiple data sources.The Canadian journal of statistics = Revue canadienne de statistique · 2024Article
- Determinants and spatial factors of anemia in women of reproductive age in Democratic Republic of Congo (drc): a Bayesian multilevel ordinal logistic regression model approach.BMC public health · 2024Article
- Multi-task Learning with High-Dimensional Noisy Images.Journal of the American Statistical Association · 2024Article
- Heterogeneity-aware Clustered Distributed Learning for Multi-source Data Analysis.Journal of machine learning research : JMLR · 2024Article
- Joint and Individual Component Regression.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2024Article
- Debiased inference for heterogeneous subpopulations in a high-dimensional logistic regression model.Scientific reports · 2023Article
- Regularization approaches in clinical biostatistics: A review of methods and their applications.Statistical methods in medical research · 2023Review
- HIGH-DIMENSIONAL FACTOR REGRESSION FOR HETEROGENEOUS SUBPOPULATIONS.Statistica Sinica · 2023Article
- A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources.Proceedings of machine learning research · 2022Article
- Meta-Analyzing Multiple Omics Data With Robust Variable Selection.Frontiers in genetics · 2021Article
- Distributed Simultaneous Inference in Generalized Linear Models via Confidence Distribution.Journal of multivariate analysis · 2020Article
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Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
As data sets of related studies become more easily accessible, combining data sets of similar studies is often undertaken in practice to achieve a larger sample size and higher power. A major challenge arising from data integration pertains to data heterogeneity in terms of study population, study design, or study coordination. Ignoring such heterogeneity in data analysis may result in biased estimation and misleading inference. Traditional techniques of remedy to data heterogeneity include the use of interactions and random effects, which are inferior to achieving desirable statistical power or providing a meaningful interpretation, especially when a large number of smaller data sets are combined. In this paper, we propose a regularized fusion method that allows us to identify and merge inter-study homogeneous parameter clusters in regression analysis, without the use of hypothesis testing approach. Using the fused lasso, we establish a computationally efficient procedure to deal with large-scale integrated data. Incorporating the estimated parameter ordering in the fused lasso facilitates computing speed with no loss of statistical power. We conduct extensive simulation studies and provide an application example to demonstrate the performance of the new method with a comparison to the conventional methods.
Indexed as
Identifiers
29056876PMC5647925What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.